Investigation efficiency SDSM model to simulate temperture indexes in arid and semi-arid regions

Climate change especially global warming is the most problem in the 21st century. So investigation variability trend this problem is very important in global, regional and local scale.Newadays numerous general circulation models(GCMs) have been designed to predicat future climat.An outstanding issu of output for regional and local applications is coarse spitial resoluation.To produce accurate predications of future climate variables at the regional and local scale various methods are suggested.Despit many studies this case, ufortunately,there is not a standard method for a specific rogion.Thus it is necessary that accurate predications of these methods are evaluated befor applaying in a certain region.One of th most widspread methods is Statistical DownScaling Model(SDSM).In this research efficiency of SDSM model is evaluated to simulate temperture indexes in Kerman station, instance arid and semi- arid regions.Hence, SDSM is calibrated and validated by using kerman station observ tempertur and national center enviromental predication data.We used mean absolute criterium to evaluate model.After obtaining confidence simulation accuracy. Temperture indexes (mean,absoluate maximmum and minimm temperture)are simulated by using two GCMs(CGCMand HadCM3 under A2 and B2 scenarios)until 2100-year.The result of this study is shown that SDSM model has suitably to simulate temperture indexes also using HadCM3 model data is beter than that of CGCM model. Increasing mean annual temperture on base HadCM3 model in (2010-2039),(2040-2069)and(2070-2100) periods relation to base period (1961-1990) is respectively 1.5,2.8 and 4.5 degree of centigrade in Kerman station.